Fuzzy inference applied to spatial load forecasting

Forecasting the future electric demand and its geographical distribution is a prerequisite to generate expansion planning scenarios. The load growth pattern is related with the urban structure and its land use. The model for simulating urban structures must be explicitly dynamic and must contains mechanisms for linking its macrostructure to micro behaviours. The paper presents a methodology which uses a fuzzy inference model over a GIS support to capture the behaviour of influence factors on the load growth pattern and map the potential for development. The load growth dynamic is simulated based on extended cellular automata in which the potential for development and demand for location in each stage drive the system into the following stage developments. By providing a series of simulation scenarios, the study unveils potential load growth maps to be used in expansion planning studies.